Configuration data import method based on smart home equipment

Abstract

The invention relates to the technical field of smart home, and discloses a configuration data import method based on smart home equipment, the method constructs a system, and the system is internally provided with a data acquisition module, a data correction module, a protocol identification module, a data processing module, a transmission stability module, an execution instruction generation module and a control module. The data acquisition module is responsible for collecting original data, the data correction module supplements and corrects the data and stores the data in an encrypted database, the protocol identification module identifies private communication protocols of different brand devices and converts the private communication protocols into a unified model, and the data processing module is used for repairing parameter analysis abnormity and evaluating processing efficiency. The transmission stability module evaluates signal quality, switches frequency bands when Wi-Fi is unstable, and repairs firmware vulnerabilities at the same time, the execution instruction generation module generates execution instructions according to results of the modules, and the control module executes the instructions to control the smart home equipment, so that configuration data import and equipment cooperative work are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart home, in particular to a configuration data import method based on smart home devices. BACKGROUND

[0002] With the rapid evolution of Internet of Things technology, smart home systems have become an important part of modern life. However, its large-scale application still faces multiple technical bottlenecks. In terms of compatibility, due to the long-term lack of unified device interconnection standards in the industry, different brands of smart home devices generally use private communication protocols (such as Zigbee, Bluetooth Mesh, Wi-Fi direct, etc.), resulting in very low interoperability between cross-brand devices. Users often encounter problems such as devices not working together and scene linkage failure in actual use, which seriously hinders the overall performance and user experience of smart home systems.

[0003] In terms of stability, the current mainstream wireless communication technology (especially Wi-Fi) has inherent defects: its star-shaped network topology relies on a single center node, which is prone to connection interruption due to signal attenuation or channel congestion; in addition, the limited penetration ability of wireless frequency bands makes devices prone to disconnection when blocked by walls. In addition, software vulnerabilities in device firmware, scheduling conflicts of system resources, and other factors further exacerbate the risk of unstable operation, directly affecting users' trust in smart home systems.

[0004] From the perspective of efficiency, traditional smart home architecture mostly adopts a cloud centralized control mode, and the configuration data generated by the device needs to be uploaded to the cloud for analysis and decision-making, and then the instructions are returned to the terminal for execution. This process not only occupies a large amount of network bandwidth, but also is limited by the response speed of the cloud service, resulting in a significant increase in operation latency. Especially in multi-device concurrent scenarios, the bottleneck effect of cloud computing is more prominent, which not only reduces data processing efficiency, but also increases the energy consumption burden of the system. The above technical bottlenecks urgently require a configuration data import solution that can break through the compatibility barriers between devices, improve local processing capabilities, and optimize data transmission paths, to promote the development of smart home systems towards high efficiency, stability, and openness. SUMMARY

[0005] (I) Technical problems solved

[0006] In view of the deficiencies of the prior art, the present application provides a configuration data import method based on smart home devices, which has the advantages of cross-protocol adaptive analysis, local and cloud collaborative processing, and multi-scene anti-interference transmission, solving the problems of cross-brand device configuration data intercommunication, wireless connection instability leading to import failure, high latency and large resource consumption in cloud transit mode.

[0007] (II) Technical solutions

[0008] In order to achieve the above object, the present application provides the following technical scheme: a configuration data import method based on smart home equipment, comprising the following steps: Step one, build a system, set data acquisition module, data correction module, protocol identification module, data processing module, transmission stability module, execution instruction generation module and control module in the system; Step two, the data acquisition module is responsible for collecting the original data of the configuration data, running state data, user operation data, environment perception data, security event data and system log data of the equipment; Step three, the data correction module supplements and corrects the collected original data, and stores the corrected data in an encrypted database; Step four, the protocol identification module identifies the private communication protocol of different brand equipment in the encrypted database, and converts non-standard configuration data into a unified general model; Step five, the data processing module is responsible for repairing parameter analysis logic exception and evaluating data processing efficiency; Step six, the transmission stability module evaluates the transmission stability according to the signal comprehensive quality calculation formula, and automatically switches to the standby frequency band when the Wi-Fi signal is unstable, while detecting and repairing firmware vulnerabilities; Step seven, the execution instruction generation module generates specific execution instructions according to the calculation results of the protocol identification module, data processing module and transmission stability module; Step eight, the control module controls the smart home equipment according to the generated execution instructions, completes the import of configuration data and the cooperative work of the equipment.

[0009] Preferably, the data acquisition module comprises a device basic information unit and a configuration data acquisition unit.

[0010] Preferably, the device basic information unit collects factory static data through the built-in chip or two-dimensional code scanning of the device; the configuration data acquisition unit collects real-time dynamic configuration data to be imported through the communication interface of the device.

[0011] Preferably, the data correction module comprises a missing data supplement unit, an abnormal data correction unit and a corrected data storage unit.

[0012] Preferably, the missing data supplement unit is built-in data integrity verification rule library, and based on the missing data inference formula of the device type, judges the missing fields in the collected dynamic configuration data, specifically:

[0013] In the formula, represents the supplemented data, represents the number of same type devices participating in calculation, represents the effective data collected, represents the average value of the same type of device in this field, represents the model matching / function similarity weight of the same type of device and the target device.

[0014] Preferably, the abnormal data correction unit corrects the abnormal data by using a parameter threshold checking formula, specifically:

[0015] In the formula, represents the corrected data, represents the original collected data, represents the preset threshold value of the field, represents the safe average value of the same type of device in this field; The corrected data storage unit creates an encrypted database for storing the standardized data processed by the data correction module.

[0016] Preferably, the protocol identification module reads the corrected data and device basic information through the protocol conversion intermediate layer, calls the vendor configuration dictionary library, and identifies the protocol type through a protocol matching formula, specifically:

[0017] In the formula, represents the protocol matching degree, represents the total number of protocol fields, represents the number of successfully matched protocol fields, when the protocol matching degree ≥ 80%, it is determined as a successful match; The protocol identification module converts non-standard data into a unified general model by using a format conversion formula, specifically:

[0018] In the formula, represents the general format data, represents the total number of parameters / fields that need to be processed when converting private format data to general format, represents the private format data, represents the field mapping coefficient, represents the correction number.

[0019] Preferably, the data processing module calculates the vulnerability risk rate , specifically:

[0020] In the formula, represents the vulnerability risk rate, represents the number of abnormal data, represents the total number of data, when the vulnerability risk rate >10%.

[0021] Preferably, the transmission stability module adopts a signal comprehensive quality calculation formula to evaluate the current transmission state, and the calculation formula is as follows:

[0022] In the formula, represents the signal quality score, represents the normalized received signal strength indication value, represents the packet loss rate, represents the channel utilization rate, and α, β and γ respectively represent the weight coefficients of RSSI, packet loss rate and channel utilization rate.

[0023] Preferably, the execution instruction generation module generates three types of instructions according to the calculation results of the protocol identification module, the data processing module and the transmission stability module: (1) Configuration data instruction: generating device parameter configuration instruction based on general format data; (2) Processing node instruction: generating data transmission node instruction based on edge-cloud distribution result; (3) Transmission control instruction: generating frequency band switching and power adjustment instruction based on signal quality evaluation result.

[0024] Compared with the prior art, the present application provides a configuration data import method based on smart home devices, which has the following beneficial effects: 1. The present application realizes accurate filling of missing fields of dynamic configuration data through the missing data filling unit by using the built-in data integrity checking rule library and the device type missing data inference formula. The missing fields are first identified by the rule library, and then the common parameters and weight calculation of the same type of device are combined to ensure that the filled data fit the actual scene of the target device (such as filling the smart light brightness parameter according to the average value of the same brand and same model), thereby avoiding configuration interruption caused by data missing; the abnormal data correction unit realizes standardized correction of abnormal data by using the preset parameter threshold range table and the parameter threshold checking formula, and corrects the original data (such as too short door lock password) according to the average security value of the same type of device, thereby ensuring the compliance and usability of the configuration data; and the corrected data storage unit realizes safe storage of standardized data by creating an encrypted database, preventing data leakage or tampering. The last three units cooperate to improve the integrity, accuracy and security of the configuration data, provide high-quality data input for protocol identification and data processing, and greatly reduce the failure risk of subsequent import links.

[0025] 2. The present application realizes protocol matching degree The compatibility of the protocol is evaluated by calculation of the protocol matching degree, when the protocol matching degree When the protocol matching degree is in the interval of 80% to 100%, the module automatically performs protocol identification and data conversion, when the protocol matching degree When the protocol matching degree is lower than 80%, the module automatically performs protocol incompatibility prompting or attempts other protocol matching, and finally achieves the effect of seamless import of configuration data of cross-brand devices; through calculation of the general format data The standardization conversion of private format data and the unified adaptation of configuration data of cross-brand devices are performed, different brand customized parameter formats are converted into a unified general model, so that the difference of data formats is eliminated.

[0026] 3, The vulnerability risk rate The security of the data is evaluated by calculation of the vulnerability risk rate, when the vulnerability risk rate When the vulnerability risk rate is in the interval of 0% to 10%, normal data processing is performed, when the vulnerability risk rate When the vulnerability risk rate is in the interval of 10% to 50%, vulnerability repair is performed, when the vulnerability risk rate Higher than 50%, data is discarded or further analyzed, and finally the method of the present application achieves the effects of improving data security and processing efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 The method flowchart of the present application. DETAILED DESCRIPTION

[0028] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0029] Please refer to Figure 1 The configuration data import method based on smart home devices comprises the following steps: Step one, constructing a system, setting data acquisition module, data correction module, main database, protocol identification module, data processing module, transmission stability module, execution instruction generation module and control module in the system; Step two, the data acquisition module is responsible for collecting configuration data, running state data, user operation data, environment perception data, security event data and system log data of the device; Step three, the data correction module performs data completion and correction, and stores the corrected data in the main database for subsequent data analysis and device configuration; Step four, the protocol identification module identifies the private communication protocols of different brand devices in the encrypted database, and converts non-standard configuration data into a unified general model, and realizes seamless import of cross-brand device configuration data according to the general calculation formula; Step five, the data processing module repairs parameter analysis logic exceptions through the calculation formula, reduces the risk of import interruption, and optimizes data processing efficiency through local edge computing and cloud lightweight collaborative architecture, reduces network bandwidth occupation and data transmission delay; Step six, the transmission stability module evaluates the transmission stability according to the signal comprehensive quality calculation formula, and automatically switches to the standby frequency band when the Wi-Fi signal is unstable, optimizes the through-wall transmission effect, and detects and repairs firmware vulnerabilities at the same time; Step seven, the execution instruction generation module generates specific execution instructions according to the calculation results of the protocol identification module, the data processing module and the transmission stability module; Step eight, the control module controls the smart home device according to the generated execution instructions, completes the import of configuration data and the collaborative work of the device.

[0030] The data acquisition module includes a device basic information unit and a configuration data acquisition unit.

[0031] The device basic information unit acquires static data of the device out of the factory through the built-in chip or two-dimensional code scanning of the device, including device brand, model, communication protocol type, hardware parameter, firmware version, supported function list, security authentication information and manufacturer reserved configuration template; The configuration data acquisition unit acquires real-time dynamic configuration data to be imported through the communication interface (such as Wi-Fi, Bluetooth, Zigbee) of the device, including the current network connection state of the device, scene linkage rule, permission parameter, user-defined device name, device running mode, timing task setting, user preference setting, device running log and real-time state data of the device.

[0032] The advantages are: through the cooperative acquisition mechanism of the device basic information unit and the configuration data acquisition unit, the device basic information unit is used to realize the accurate acquisition of the static data of the whole life cycle of the device, and the built-in chip reading and two-dimensional code scanning are combined to complete the acquisition of the core parameters (such as hardware parameters, security authentication information) of the device out of the factory, which provides a basis for subsequent protocol identification and data processing, so as to avoid the adaptation failure caused by the lack of device basic information; The configuration data acquisition unit is used to realize the real-time and multi-dimensional capture of dynamic configuration data of the device, to capture dynamic data such as network state, user preference and timing task, and cover all scene information required by device configuration; Finally, it achieves the beneficial effect of providing complete and accurate data source for the whole configuration data import process, reduces the import errors caused by incomplete or lagging data from the source, and lays a data foundation for the efficient operation of the subsequent modules.

[0033] The data correction module comprises a missing data completion unit, an abnormal data correction unit and a corrected data storage unit.

[0034] The missing data completion unit is built-in with a "data integrity verification rule library" (such as judging "Wi-Fi password field is not empty" and "linkage rule contains trigger condition and execution action"), and based on the missing data inference formula of the device type, it judges the fields that are missing in the collected dynamic configuration data (and the field can be derived through the common parameters of the same type of device). Specifically:

[0035] In the formula, represents the completed data, represents the number of same type devices participating in the calculation (i.e. the total number of device samples used to provide common parameter reference), represents the collected valid data, represents the average value of the same type device field (such as the average value of the "response delay" of the same brand intelligent switch), represents the "model matching degree / functional similarity" weight of the same type device and the target device (value range 0.1-1.0, the higher the matching degree and the more similar the function, the greater the weight), which is used to accurately measure the reference value of the same type device data for the missing field of the target device; Embodiment 1 When the collected intelligent lamp brightness parameter is missing, the average brightness of the same brand and same model intelligent lamp (such as 500 lm) is calculated through the missing data inference formula of the device type to complete the field.

[0036] The abnormal data correction unit is pre-set with a "parameter threshold range table" (such as device alarm delay 1-60 seconds, Wi-Fi frequency band 2.4GHz / 5GHz), and uses a parameter threshold verification formula to correct abnormal data. Specifically:

[0037] In the formula, represents the corrected data, represents the original collected data, represents the pre-set threshold of the field (such as "alarm delay" 1-60 seconds), represents the safe average value of the same type device field; Embodiment 2 When the "door lock password length = 3 digits" (pre-set threshold 6-12 digits) is collected, it is corrected to the average value of the same brand door lock password length (such as 8 digits); The modified data storage unit creates an encrypted database (using AES-256 encryption) for storing standardized data processed by the data modification module.

[0038] The advantages are: through the above-mentioned missing data completion, abnormal data modification and encrypted storage of the whole-process data optimization mechanism, the missing data completion unit realizes accurate completion of missing data fields through built-in data integrity check rule library and device type missing data inference formula, identifies missing fields through the rule library first, and then combines common parameters and weight calculation of the same type of device to ensure that the completed data fits the actual scene of the target device (such as the brightness parameter of the smart lamp being completed according to the average value of the same brand and same type), thereby avoiding configuration interruption caused by data missing; the abnormal data modification unit realizes standardized modification of abnormal data through a pre-set parameter threshold range table and a parameter threshold check formula, and modifies the original data (such as a too short door lock password) according to the average security value of the same type of device when the threshold is exceeded, thereby ensuring the compliance and usability of the configuration data; and the modified data storage unit realizes safe storage of standardized data by creating an encrypted database to prevent data leakage or tampering. The last three units work together to improve the integrity, accuracy and security of the configuration data, provide high-quality data input for protocol identification and data processing, and greatly reduce the failure risk of subsequent import links.

[0039] The protocol identification module identifies the private communication protocols of different brand devices and converts non-standard configuration data into a unified general model to realize seamless import of cross-brand device configuration data according to a general calculation formula, which is: The protocol conversion intermediate layer reads the modified data and device basic information, calls the vendor configuration dictionary library, and identifies the protocol type through a protocol matching formula, the calculation formula of which is:

[0040] In the formula, represents the protocol matching degree, represents the total number of protocol fields, represents the number of matched protocol fields, when ≥80%, it is determined that the matching is successful (such as the data to be parsed containing "Zigbee address" and "cluster ID" fields, with a Zigbee protocol field matching degree of 90%, it is determined that it is a Zigbee protocol; The non-standard data is converted into a unified general model using a format conversion formula, the calculation formula of which is:

[0041] In the formula, represents the general format data, Total number of parameters / fields to be processed when converting private format data to general format, Private format data, Field mapping coefficient (e.g. the coefficient for converting A brand "switch_delay_ms" to general "delay_time_s" is 0.001), Correction number, adjusted according to manufacturer format deviation.

[0042] Advantages: Through the calculation of the above protocol matching degree , the compatibility of the protocol is evaluated, when the protocol matching degree is in the interval of 80%~100%, the module automatically performs protocol recognition and data conversion, when the protocol matching degree is less than 80%, the module automatically prompts the incompatibility of the protocol or tries other protocol matching, and finally achieves the effect of seamless import of cross-brand device configuration data; through the calculation of general format data , the standardized conversion of private format data and the unified adaptation of cross-brand device configuration data are carried out, and the parameter format customized by different brands is converted into a unified general model, so as to eliminate the difference of data format.

[0043] The data processing module calculates the vulnerability risk rate to repair the abnormal parameter analysis logic, reduce the interruption risk in import, and optimize the data processing efficiency through the "local edge computing + cloud lightweight cooperation" architecture, reduce the network bandwidth occupation and data transmission delay;

[0044] In the formula, represents the vulnerability risk rate, represents the number of abnormal data, represents the total number of data, when the vulnerability risk rate >10%, the module automatically calls "vulnerability repair algorithm" (such as replacing the wrong field type, supplementing the missing syntax symbol); Embodiment 3 When the data to be imported contains "linkage rule without execution action" (the exception is recorded in the vulnerability feature library), when the vulnerability risk rate >15%, then "execution action=turn on the light" is automatically supplemented.

[0045] Advantages: Through the calculation of the vulnerability risk rate , the security of the data is evaluated, when the vulnerability risk rate is in the interval of 0%~10%, normal data processing is performed, when the vulnerability risk rate is in the interval of 10%~50%, vulnerability repair is performed, and when the vulnerability risk rate When the signal quality score is higher than 50%, data discarding or further analysis is performed, and finally the method of the application achieves the effects of improving data security and processing efficiency.

[0046] The transmission stability module uses a signal comprehensive quality calculation formula to evaluate the current transmission state, and the calculation formula is as follows:

[0047] In the formula, represents the signal quality score, represents the normalized received signal strength indication value (mapping the original RSSI from dBm to the 0-1 interval, such as through linear transformation, represents the packet loss rate (Packet Loss Rate), that is, the proportion of data packet loss (0≤PLR≤1), represents the channel utilization rate (Channel Utilization Rate), that is, the proportion of current channel bandwidth occupation (0≤CUR≤1), and α, β and γ respectively represent the weight coefficients of RSSI, packet loss rate and channel utilization rate.

[0048] The advantage is that the transmission stability is evaluated through the calculation of the signal quality score When the signal quality score is in the high interval, normal data transmission is performed, when the signal quality score is in the medium interval, frequency band switching or power adjustment is performed, when the signal quality score is in the low interval, error retransmission or interrupted transmission is performed, and finally the effects of optimizing transmission and improving data transmission success rate are achieved.

[0049] The execution instruction generation module generates three types of instructions according to the calculation results of the protocol identification module, the data processing module and the transmission stability module: (1) Configuration data instruction: based on general format data, generate device parameter configuration instruction (such as bedroom lamp brightness = 50%); (2) Processing node instruction: based on the edge-cloud distribution result, generate data transmission node instruction (such as local gateway receiving device name data); (3) Transmission control instruction: based on the signal quality evaluation result, generate frequency band switching and power adjustment instruction (such as switching to Bluetooth Mesh frequency band, transmission power 18dBm); And the three types of instructions are packaged and transmitted to the configuration import control module; The configuration import control module includes a device configuration execution unit, a transmission control unit and a node coordination unit, and performs configuration and monitoring, specifically: (1) Device configuration execution unit sends configuration data instructions to target devices to execute parameter writing (such as writing "brightness = 50%" to smart lights); (2) Transmission control unit: adjust the communication module parameters of the central control platform according to the transmission control instructions (such as switching frequency bands and improving power); (3) Node coordination unit: coordinate the data interaction between the local gateway and the cloud according to the processing node instructions (such as synchronizing local processing results to the cloud backup); And record the import progress of each device in real time, when import failure occurs (such as device no response), the module automatically triggers retry instruction (retransmit based on stable transmission parameters of step six); The advantages are: through the configuration import control module to complete the configuration data import of all devices, to realize the cooperation of cross-brand devices, stable wireless connection and processing efficiency improvement (the time consumption of multi-device concurrent import is shortened from 30 minutes to 12 minutes), so as to solve the compatibility, stability and efficiency problems in the prior art.

[0050] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and modifications can be made to these embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for importing configuration data based on smart home devices, characterized in that, The method comprises the following steps: Step one, constructing a system, setting up a data collection module, a data correction module, a protocol identification module, a data processing module, a transmission stability module, an execution instruction generation module and a control module in the system; Step two, the data collection module is responsible for collecting the original data of the configuration data, the running state data, the user operation data, the environment perception data, the safety event data and the system log data of the equipment; Step three, the data correction module corrects and supplements the collected original data, and stores the corrected data in an encrypted database; Step four, the protocol identification module identifies the private communication protocols of different brands of equipment in the encrypted database, and converts non-standard configuration data into a unified general model; Step five, the data processing module is responsible for repairing parameter analysis logic exceptions and evaluating data processing efficiency; Step six, the transmission stability module evaluates the transmission stability according to the signal comprehensive quality calculation formula, and automatically switches to the standby frequency band when the Wi-Fi signal is unstable, while detecting and repairing firmware vulnerabilities; Step seven, the execution instruction generation module generates specific execution instructions according to the calculation results of the protocol identification module, the data processing module and the transmission stability module; Step eight, the control module controls the smart home equipment according to the generated execution instructions, completes the import of configuration data and the collaborative work of the equipment. 2.The smart home device-based configuration data import method of claim 1, wherein: The data collection module comprises an equipment basic information unit and a configuration data collection unit. 3.The smart home device-based configuration data import method of claim 2, wherein: The equipment basic information unit collects the factory static data of the equipment through the built-in chip or two-dimensional code scanning of the equipment; The configuration data collection unit collects real-time dynamic configuration data to be imported through the communication interface of the equipment. 4.The smart home device-based configuration data import method of claim 1, wherein: The data correction module comprises a missing data supplement unit, an abnormal data correction unit and a corrected data storage unit. 5.The smart home device based configuration data import method of claim 4, wherein: The missing data supplement unit has a built-in data integrity verification rule library, and judges the missing fields in the collected dynamic configuration data based on the missing data inference formula of the equipment type, specifically: In the formula, represents the data after padding, represents the number of same type devices participating in the calculation, represents the effective data collected, represents the average value of the same type device in this field, represents the model matching degree / function similarity weight of the same type device and the target device. 6.The smart home device based configuration data import method of claim 1, wherein: The abnormal data correction unit corrects the abnormal data by using the parameter threshold verification formula, specifically: In the formula, represents the corrected data, represents the original collected data, represents the preset threshold of the field, represents the security average value of the field of the same type of device; The corrected data storage unit creates an encrypted database for storing standardized data processed by the data correction module. 7.The smart home device based configuration data import method of claim 1, wherein: The protocol identification module reads the corrected data and equipment basic information through the protocol conversion intermediate layer, calls the vendor configuration dictionary library, and identifies the protocol type through the protocol matching formula, specifically: In the formula, represents the protocol matching degree, represents the total number of protocol fields, represents the number of protocol fields that are successfully matched, when the protocol matching degree ≥80%, it is determined that the matching is successful; The protocol identification module converts non-standard data into a unified general model by using the format conversion formula, specifically: In the formula, represents general format data, represents the total number of parameters / fields to be processed when converting private format data into general format, represents private format data, represents a field mapping coefficient, represents a correction constant. 8.The smart home device based configuration data import method of claim 1, wherein: The data processing module calculates a vulnerability risk rate , in particular; In the formula, represents the vulnerability risk rate, represents the number of abnormal data, represents the total number of data, when the vulnerability risk rate > 10%. 9.The smart home device based configuration data import method of claim 1, wherein: The transmission stability module uses the signal comprehensive quality calculation formula to evaluate the current transmission state, and the calculation formula is: In the formula, represents a signal quality score, represents a normalized received signal strength indication value, represents a packet loss rate, represents a channel utilization rate, and α, β, and γ respectively represent weight coefficients of RSSI, the packet loss rate, and the channel utilization rate. 10.The smart home device based configuration data import method of claim 1, wherein: The execution instruction generation module generates three types of instructions according to the calculation results of the protocol identification module, the data processing module and the transmission stability module: (1) Configuration data instruction: based on general format data, generate device parameter configuration instruction; (2) Processing node instruction: based on edge-cloud distribution results, generate data transmission node instruction; (3) Transmission control instruction: based on signal quality evaluation results, generate frequency band switching and power adjustment instructions.

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